Elder Abuse: Selected Papers from the Prague World Congress on Family Violence
Bibliographic record
Abstract
* Foreword * Introduction * Grandparents Raising Grandchildren: The Risks of Caregiving (Patricia Brownell, Jacqueline Berman, Antoinette Nelson, and Rosemary Colon Fofana) * The Elder Abuse of Custodial Grandparents: A Hidden Phenomenon (Jordan I. Kosberg and Gordon MacNeil) * Combating Elder Financial Abuse--A Multi-Disciplinary Approach to a Growing Problem (Betty Malks, Jamie Buckmaster, and Laura Cunningham) * Study of Elder Abuse Within Diverse Cultures (Jordan I. Kosberg, Ariela Lowenstein, Juanita L. Garcia, and Simon Biggs) * A National Look at Elder Abuse Multidisciplinary Teams (Pamela B. Teaster, Lisa Nerenberg, and Kim L. Stansbury) * A Forensic Medical Examination Form for Improved Documentation and Prosecution of Elder Abuse (Diana Koin) * Elder Abuse Awareness in Faith Communities: Findings from a Canadian Pilot Study (Elizabeth Podnieks and Sue Wilson) * An Exploratory Study of Responses in Elder Abuse in Faith Communities (Elizabeth Podnieks and Sue Wilson) * Older Women, Domestic Violence, and Elder Abuse: A Review of Commonalities, Differences and Shared Approaches (Bridget Penhale) * Elder Abuse Risk Indicators and Screening Questions: Results from a Literature Search and a Panel of Experts from Developed and Developing Countries (Christen L. Erlingsson, Sharon L. Carlson, and Britt-Inger Saveman) * Index * Reference Notes Included
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".